Revealing the Black Box of Privacy Concern: Understanding How Self-disclosure Affects Privacy Concern in the Context of On-Demand Services Through Two Competing Models

Abstract

As a prevalent economic paradigm, on-demand services match service providers and consumers with respective needs through the on-demand service platform. Consumers have to express their needs through self-disclosure, which inevitably raises privacy concern. However, how consumers’ self-disclosure influences their privacy concern has not been well studied and remains as a black box. In this study, we would like to investigate how consumers’ prior self-disclosure affects their privacy concern through two competing models derived from two theories in the literature: prominence interpretation theory and information processing theory. Based on prominence interpretation theory, the first model explains how the amount of consumers’ prior self-disclosure in the past use affects the prominence and interpretation of requests for self-disclosure, thus finally influences consumers’ privacy concern about their information. Based on information processing theory, the second model proposes a two-step approach that the amount of consumers’ prior self-disclosure in the past use affects consumers’ beliefs in the first step, and in the second step consumers’ beliefs impact their evaluation of the on-demand service platform, thus finally influence their privacy concern. The models will be tested based on survey data collected from on-demand service consumers. The potential theoretical contributions and practical implications for consumers, service providers, and platforms are discussed.